Gen AI Lead

Good co India; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

Good co India in the United States seeks a Senior GenAI Lead to define and execute the Generative AI strategy and technical roadmap. You will architect GenAI solutions, lead end-to-end development, and drive AI-enabled business outcomes across teams.

Responsibilities include leading prompt engineering, model evaluation, and building scalable architectures with vector databases, cloud platforms, and MLOps practices. Strong collaboration and cloud experience are essential.

Qualifications

• Hands-on Generative AI implementation experience.
• Experience with LLMs and foundation models.
• Knowledge of RAG, embeddings, vector databases.
• Experience deploying production AI apps on cloud platforms.
• Ability to lead technical teams across cross-functional partners.

Responsibilities

• Define and implement Generative AI strategy, roadmap, and architecture.
• Lead design, development, testing, deployment of GenAI solutions with LLMs.
• Build and optimise RAG pipelines, AI agents, chatbots, automation.
• Evaluate and integrate LLMs for business use cases.
• Lead prompt engineering, model evaluation, benchmarking, performance tuning.
• Design scalable AI architectures using vector databases, APIs, cloud platforms.
• Establish MLOps/LLMOps for deployment, monitoring, versioning.

Skills

Python

Analytical thinking

Problem solving

Communication

Stakeholder management

Education

Bachelor's degree in Computer Science/IT/AI/Data Science

Master's degree in AI/ML/CS/Data Science (preferred)

Tools

PyTorch

TensorFlow

LangChain

LangGraph

AWS

Azure

Google Cloud Platform

Docker

Kubernetes

CI/CD

Job description

Role & responsibilities

• Define and implement the Generative AI strategy, technical roadmap, and architecture aligned with business objectives.
• Lead the design, development, testing, and deployment of GenAI solutions using LLMs and foundation models.
• Build and optimise RAG pipelines, AI agents, chatbots, and intelligent automation systems.
• Evaluate, select, fine-tune, and integrate LLMs for specific business use cases.
• Lead prompt engineering, model evaluation, benchmarking, and performance optimisation.
• Design scalable AI architectures using vector databases, APIs, cloud platforms, and distributed systems.
• Establish MLOps/LLMOps practices for model deployment, monitoring, versioning, and continuous improvement.
• Ensure AI solutions meet requirements for data privacy, security, reliability, responsible AI, and regulatory compliance.
• Collaborate with product, engineering, data science, and business teams to identify and deliver high-impact AI use cases.
• Manage technical project delivery, resource allocation, and stakeholder expectations.
• Mentor AI/ML engineers and establish best practices for GenAI development.
• Track emerging AI technologies and drive innovation, cost optimisation, and measurable business outcomes.

Preferred candidate profile

• Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
• Master's degree in AI/ML, Computer Science, or Data Science preferred but not mandatory.
• 5 to 10 years of experience in software engineering, machine learning, AI, or data science, with hands‑on Generative AI implementation experience.
• Strong programming skills in Python and experience with frameworks such as PyTorch, TensorFlow, LangChain, or LangGraph.
• Practical expertise in LLMs, RAG, embeddings, vector databases, prompt engineering, fine‑tuning, and AI agents.
• Experience deploying production‑grade AI applications using AWS, Azure, or Google Cloud Platform.
• Knowledge of Docker, Kubernetes, CI/CD, MLOps/LLMOps, model monitoring, and scalable system architecture.
• Strong understanding of AI evaluation, hallucination mitigation, guardrails, data security, and responsible AI practices.
• Proven ability to lead technical teams, manage projects, and collaborate across cross‑functional teams.
• Excellent analytical, problem‑solving, communication, and stakeholder management skills.
• Ability to translate business requirements into secure, reliable, cost‑effective, and scalable GenAI solutions.